Problem Description

Over the past few years there has been much publicity about the
possibilities of tissue engineering and regenerative medicine
producing new and exciting treatments for a whole range of diseases
and injuries. One difficulty is scaling up laboratory based cell and
tissue culture into high throughput systems that could meet the
demands of regenerative therapies.

One of the main purposes of cell culture is multiplication of cell
numbers to produce appropriate quantities for therapy. In practice,
there are only a certain number of cells that can be effectively grown
in a given flask before they are no longer functional. Thus, once a
flask has reached its capacity its cell population is split into
multiple flaks and sub-cultured. This process is called passaging and
it is important that passaging occurs when the cells are in their most
proliferative state. Currently the point of passage is determined very
subjectively. On a laboratory scale culture flasks are visually
inspected to assess the area of the plate covered, cell connectivity
and cell distribution.

The problem for the study group is development of a mathematical
model to predict cell multiplication during culture with the aim of
identification of the point of passage.

Study Group Report

In this Study Group report a number of models of growing cell
populations are considered. We first used a logistic growth model for
a single cell type. We found that for small growth rates,
k, it is possible to passage at lower passaging
confluences, as the delay time, ts, is small in
comparison to the growth time. For larger growth rates it is necessary
to passage as few times as possible, because the delay time is large
in comparison to the growth time. Therefore, it is optimal to passage
at higher confluence.

We then considered presented a logistic growth model for multiple
cell types. Here we noted that we should minimise the number of
passages, np, as well as the time taken,
T, to obtain the required number of cells,
Nmax. For the simulation run we found good
agreement with current tissue engineering protocol. Further work could
be carried out on this model, with consideration given to how the
results shown vary for dierent growth rates, k.

Finally we introduced a spatial model which we were unable to
investigate within the scope of the Study Group. Further work on this
model obviously exists and would be of interest to investigate.